Enterprise resource planning (ERP) is a business management software typically used to collect, store, manage, and interpret data from various business activities such as, for example, expenses made by employees of an enterprise. ERP systems generally collect data related to business activities of various departments in an enterprise. Such collected data may come from different data sources, and may be in different formats. ERP systems provide an integrated view of this business activity data, and further enable generation of expense reports that can later be sent to the relevant tax authority.
Especially in large enterprises, employees engage in a high number of business activities. Such business activities may further result in a large number of business expenses to be reported to tax authorities. Reporting such business expenses may result in tax breaks and refunds. To this end, employees typically provide receipts based on expenses incurred and are usually required to indicate the types of such expenses. Based on the indication, an ERP system may generate a report which is provided with any received receipts to the relevant tax authority.
Additionally, pursuant to managing the data related to business activities, ERP systems must associate and track relations between sets of the managed data. For example, information related to tax reporting of a receipt must be maintained with an association to the receipt itself. Any errors in associations between data sets can result in incorrect reporting, which in turn may cause loss of profits due to unsuccessful redemptions and exemptions, and failure to comply with laws and regulations. Thus, accurate data management is crucial for ERP systems.
Tracking such data presents additional challenges when portions of the data are unstructured. For example, there are further difficulties associated with tracking expense receipts stored as image files. Some existing solutions to these challenges involve identifying contents of files containing unstructured data based on file extension names provided by users. Such solutions are subject to human error (e.g., typos, mistaking contents of files, etc.), and may not fully describe the contents therein. These disadvantages may further contribute to inaccuracies in ERP systems.
The number of receipts obtained by employees in the course of business may be tremendous. This high number of receipts results in significant increases in data provided to ERP systems, thereby leading to difficulties managing the data in such ERP systems. Specifically, existing solutions face challenges in finding and maintaining correct associations within the managed data. These difficulties may result in errors and mismatches. When the errors and mismatches are not caught in time, the result may be false, related to a plurality of evidences or otherwise incorrect reporting. Manually verifying that reports match receipts is time and labor intensive, and is subject to human error. Further, such manual verification does not, on its own, correct issues with the managed data.
Additionally, existing solutions for automatically verifying transactions face challenges in utilizing electronic documents containing at least partially unstructured data. Specifically, such solutions may be capable of recognizing transaction data in scanned receipts and other unstructured data, but may be inefficient and inaccurate when utilizing the recognized transaction data.
It would therefore be advantageous to provide a solution that would overcome the deficiencies of the prior art.